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'McLaughlin has given us an original and daring account of functional explanation [his] fascinating account of organisms as self-maintaining systems is.
Table of contents
Populations of agents containing the mechanism outcompete populations lacking it i. The mechanism works because the low probability of successful change is compensated, on average, by the probabilistic prospect of fast, exponential growth in numbers. This growth follows when x and thus f is high enough. Even if many organisms will perish, the remaining ones can thrive and multiply. The mechanism of the G loop is remarkable, because it utilizes randomness in a way that thoroughly mixes random and deterministic factors. In effect, it transfers determinacy by varying randomness. The outcome of a hereditary or behavioral trajectory that results from many G loop cycles is, therefore, unpredictable in detail.
Yet, the long-term course of a trajectory is not completely random, because it is driven by x. At the behavioral timescale, such a combination of indeterminate and determinate factors is the signature of agency van Hateren a ; agency is taken here as the ability to initiate behavior that is significant to the agent itself. In effect, the mechanism provides the agent with some behavioral freedom.
The agent or, its lineage appears to be driven into the direction of high x and thus, quite probably, high f as well. But this happens without explicit, foreseen directionality. The directionality is purely the statistical consequence of a random, probabilistic process. The G loop lets the behavior of the agent or, the heredity of the agents in a lineage drift away quickly from structures with low x, because low x produces large behavioral or, hereditary variability.
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X is part of the agent and it originates within the agent through random modifications. Modifications of X affect fitness, through which they are, implicitly, evaluated. Importantly, the ultimate causal efficacy of X depends on the condition that x approximates fitness.
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This approximating relationship between x and f i. It has causal efficacy in addition to the direct proximate causal efficacy of the material parts of X. In particular, the model implies that the material parts of X can only affect fitness if the non-material relation between x and f is present as well. The latter is partly independent of X, because the relation not only depends on x, but also on F and f which can vary autonomously and, to some extent, randomly. Therefore, both causal aspects of X are needed in conjunction, and they can be regarded as complementary.
They produce neither epiphenomenalism, nor causal overdetermination. The autonomous causal efficacy of the relation between x and f gives an ontic-causal status to x. Its relation with f needs to be included in a complete and minimal causal inventory of the world. As stated above, f itself is an epistemic-real construct that is fully defined by its microscopic constituents and their interactions.
Readers may be puzzled by the fact that x obtains ontic-causal status by being related to an epistemic-real f. However, one should realize that the relation between x and f is not based on a regular physicochemical connection. Rather, it is an approximating relationship that cannot be defined in terms of physicochemical constituents. Properties of f do not transfer to x, just like the properties of the weather e. The weather and its simulation belong to different categories. The approximating relationship between x and f is an emergent, nonmaterial factor with causal efficacy.
The drive towards high x must be regarded, then, as the implicit goal of the agent van Hateren a. The agent combines this goal-directedness with the behavioral freedom provided by agency. Agency makes it possible that the agent changes its behavior in a direction away from the goal i.
The strength of attraction towards the goal must be equated, then, to the value that the agent implicitly attaches to the goal. The goal of high x is implicitly normative, for the agent itself van Hateren d. The agent is expected to strive for high x, intrinsically. It is supposed to strive for high x not from the point of view of any external agent, but from the point of view of the agent itself. Thus, the G loop produces primordial forms of agency, goal-directedness, and normativity, as emergent factors.
Moreover, it also produces a primordial form of causally effective reference, because X is causally effective only because x implicitly refers to f in the form of an approximating relationship.
Whereas reference plays no causal role in abiotic nature, it is present in systems if and probably only if these contain an X process. Because X presupposes evolution, such systems must be living organisms. As argued above, high x must be regarded as the overall goal of an agent. But in practice, the process X is decomposed into subprocesses that serve specific subgoals, such as having a well-functioning heart, finding food, and finding mates. Together, these subprocesses and subgoals contribute to X and x. The intrinsic goals of the agent are completely defined by X. New goals are, by definition, incorporated into an accordingly changed X.
Because X has a nonmaterial causal aspect in the form of the relation between x and f , its subprocesses also have a nonmaterial causal aspect in the form of the relation between their subgoals and the corresponding parts of F. Subprocesses that monitor specific functions then produce a causal efficacy that goes beyond that of the material realization of the functions themselves.
Similarly, the way in which X modulates variability as based on x is also decomposed into subprocesses affecting different parts of the agent differentially. If x is low because a specific trait is malfunctioning, variability need not and will not in general be redirected to that specific trait. How variability is redirected and distributed in specific organisms is likely to be quite complex, depending on the particulars of the organism and its habitat.
However, the way in which X distributes variability is readily evolvable through standard evolutionary mechanisms, because it affects f. It is therefore likely to be adequate, on average. As an example of how variability may be redirected, we can consider the function of hemoglobin in vertebrates.
It has the function of enhancing oxygen transport, according to existing theories of biological function. The new theory ascribes this function to hemoglobin as well, as follows.
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If hemoglobin starts to work less effectively, such as in the presence of interfering chemicals, then this is detected by control circuits regulating the oxygen levels in an organism. Compensatory changes e. The new theory conjectures that a deficient oxygen level produces, in addition, effects through X. The oxygen level is one of the factors likely to be used for producing such an overall fitness estimate, because this level is highly significant for the actual fitness.
Therefore, X has likely evolved to include it, because that improves the adequacy of x as an estimator of fitness. Therefore, a poor performance of hemoglobin reduces x, and thus, indirectly, drives more variability anywhere in the organism. For example, it may result in behavioral variations that eventually result in the organism finding a less energetic lifestyle. Such a lifestyle can enable it to survive, despite suboptimal oxygen levels. The new lifestyle can become fixed through a reduction of behavioral variability , because X subsequently indicates that the expected i.
In conclusion, biological functions can acquire ontic-causal status as follows. If a trait, process, or behavior is of evolutionary significance to an agent, for example the pumping of blood by the heart, then it is likely to be represented in X. This is likely, because X would need to monitor the blood circulation in order to produce an x that is a reasonable approximation of f.
A poorly working blood circulation should be reflected in a decreased x. A reasonable approximation of f by x is required for obtaining high fitness through the mechanism of the G loop. It is therefore under positive selection pressure.
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We have seen above that subprocesses of X have autonomous causal efficacy, that is, they are ontic-causal. Therefore, the function as such is also ontic-causal. It has a non-material causal aspect through X that occurs in addition to the material realization of the function itself such as is realized by the heart and its muscles.
In order to decide whether a trait or process is functional in the ontic-causal sense, one needs to determine whether it is represented in X, that is, whether it is monitored by X and thus used for producing x and for modulating organismal variability. Whether a trait or process is monitored by X is ultimately an empirical question. X is just a physiological or neural process that can be identified and modeled, including if and how it tracks the performance of specific traits or processes.
If X exists as conjectured here , it must be included in any adequate model of the organism. When a good model of X is established, then this also establishes what is represented in X and what not. Until such empirical and modeling studies are available, common sense arguments may be used to evaluate the proposal made in this article see, e. The key notion here is that X itself has evolved and is subject to continuing evolutionary pressure.
If x approximates f well, it gives the organism an evolutionary advantage. But like any biological process, X is costly e.